Misspecification tests of individual assumptions underlying regression models often lead to erroneous conclusions regarding source of misspecification. Monte Carlo experiments demonstrate that a comprehensive set of individual and joint tests reduces the likelihood of such conclusions. A practical testing strategy is proposed and suggestions made regarding its implementation.
The size of R2 and R̅2 are poor specification indicators since correctly specified models can have “low” R2 values and misspecified models often have “high” R2 values. Further, R2 and R̅2, as typically calculated, are found to be inconsistent measures of goodness of fit whenever the mean of the dependent variable is not stationary. Consistent estimation methods are proposed.
The purpose of this research project was to evaluate the differences and potential strengths and weaknesses of different methods for evaluating consumers' willingness to pay for a public good, i.e., a flood hazard reduction project. Three methods are compared and contrasted both collectively and against the theory of revealed consumer preference. These are the Property Damages Avoided (PDA) approach, Hedonic Price Method (Land Price Analysis), and the Contingent Value Method (CVM). The report consists of nine sections, a bibliography, and two appendices. The sections provide historical and other situational background information on the location of the proposed project, an overview of the revealed preference approach and P&G guidance for evaluating willingness to pay, a detailed description of each method and its application in the study, and the resulting findings. The first appendix displays the contingent valuation survey forms and procedures used, while the second appendix presents the questions asked to subject consumers of the study concerning a bond referendum to pay for the proposed project.
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